# Business Plan Writing

Documenting the opportunity, model, market, operations and financials — as much a thinking discipline as a document.

**Rests on:** SWOT Analysis

**Leads to:** Business Model Design

*Business, Career and Human Factors · Entrepreneurship*


## Why learn this

Writing a business plan is the thinking discipline that forces you to test every assumption of your venture before you spend money or time on it. It is the bridge between an idea and an opportunity — the moment you put numbers on 'people will pay for this', you discover whether it is true. Master this, and you unlock the rest of entrepreneurship: Business Model Design (what you actually sell and how you charge for it), Startup Financing (why investors will and won't write you a cheque), Cash Flow Management (why profit doesn't keep you alive), and eventually the paths out — Franchising, Family Business Succession, or Exit and Selling. Every one of those topics assumes you can answer the questions this plan asks first.


## The intuition

You are standing with a friend at a railway station in Delhi. You point at a stall selling hot samosas and say, 'We should do that.' Your friend asks three questions. First: 'Who is our customer at 7 am — the commuter rushing to the platform, or the driver waiting for the next shift to start?' Second: 'What do we have to buy every morning — flour, potatoes, oil, gas — and how many samosas must we sell before we break even on the rent of the stall?' Third: 'If we are not there for three days, does the stall still run, or does it shut down because only we know how to fry the samosas?'

A business plan is the act of sitting down and answering those kinds of questions in writing — not in your head, and not in an enthusiastic conversation with your cousin late at night. The questions are dull. The ingredients cost what they cost. The rent is what it is. But the discipline of forcing yourself to write down the numbers — how many samosas at how many rupees each on how many days a week — is what separates an idea from an opportunity. An idea is free. An opportunity is an idea that someone has proven they will pay for, at a price that covers your costs, on a schedule you can survive.

The plan itself, the document, is often never read — you write it to find the holes in your own thinking. The value is in the reasoning it forces, not the artifact produced. Every financial projection you calculate is an assumption wearing a costume. When you see 'we will sell 500 samosas a day in month three,' your brain treats it as a fact; your spreadsheet does not care, but your plan should ask: on what evidence? Have we stood at the station and counted? Have we asked the current stall owner what they sell on an average Tuesday? This is why the plan exists — to turn 'we think' into 'we know' or 'we need to check.'


## An analogy

A business plan is like a map you draw of a jungle before you walk into it, knowing full well that the map will be wrong.

Imagine you are a surveyor at the edge of a dense forest. You can see a clearing about a kilometre in — you think there might be fresh water there, and you want to set up a camp. You could just start walking. That is the 'launch a business' approach most people take. You will quickly discover the swamp you didn't know about, the river that blocks you, the hill that takes three days to climb instead of one. You might reach the clearing — or you might not, and you will never know if you were on the right track.

Alternatively, you climb the tallest tree near the edge. From there you can see the swamp, the river, the hill. You sketch a rough map. You mark the obstacles you can see and you mark unknown areas as 'assume the worst.' The map takes you a day to draw. This is the business plan.

Where the analogy holds: the map does not make the jungle less dangerous, but it makes your choices better. You choose to go around the swamp before you sink into it. You budget three days for the hill instead of being surprised. You decide, based on the map, that the clearing is not actually worth the river crossing — and you find a different clearing. The plan is a tool for deciding before you are waist-deep.

Where the analogy breaks down: a jungle stays the same while you walk through it. A market does not. While you are drawing your plan, a competitor opens a stall selling tea next to your planned samosa counter. A supplier doubles the price of oil. A pandemic closes the station for six months. The map is wrong the moment it is drawn, because the terrain moves. This does not make the map worthless — it makes it a living document, revised every week. Cargo cult businesses are the ones that write a plan once, file it in a drawer, and never look at it again. The map is valuable only if you keep redrawing it.


## Definition

A business plan is a written document that captures the opportunity you see, the model you will use to capture it, the market you are selling to, the operations that will deliver it, and the financial projections that test whether the whole thing can make money — and it functions as a thinking discipline that forces you to make your assumptions explicit and test them.


## How it connects

This concept sits right at the centre of everything you have noted about entrepreneurship. It is the discipline that precedes and feeds all the others.

It connects most directly to **Business Model Design** — your plan's 'revenue model and cost structure' section is where you decide whether scale helps or hurts. If your fixed costs (rent, equipment) are high and your variable costs (materials, labour per item) are low, then selling more makes you more profitable per unit — scale helps. If your costs rise proportionally with every sale, scale does not rescue you. Your plan forces this into the open.

It connects to **Startup Financing** — at every funding stage, from family loan to venture capital, the person with the money asks 'show me the plan.' They are not reading it for the prose; they are reading the financials to judge whether you have been honest with yourself. The four sources you noted (bootstrapping, debt, equity, grants) each demand a different kind of plan — a bank wants cash flow and collateral; an angel investor wants the market story and the exit.

It connects to **SWOT Analysis** — a plan's market section is essentially where you make your SWOT external: opportunities and threats live here, where your competitors and customers actually are. The plan forces the external view that the SWOT framework exists to demand.

It connects to **Business Acquisition**. Your notes record the four-step path: raise capital, identify targets, fund the buyout, create value. Writing a plan for an acquisition is exactly the same discipline — what the target brings, how you will create value, and what the numbers say — but multiplied by the risk of inheriting someone else's hidden problems, which is why your notes also record that due diligence quality determines whether the price was right.

It connects to **Crowdfunding** — your notes say a campaign validates demand and raises money at the same time, and that it is a marketing exercise as much as a financing one. The plan is what you rewrite as the pitch page: the numbers, the market, the promise, compressed for strangers.

It connects to **Exit and Selling** — your notes record that a business dependent on its owner is difficult to sell, and valuation depends on transferable, documented cash flow. The plan is the documentation. If you have written down how the business runs — operations, staffing, customer relationships — then the business is not trapped in your head, and it has a documented cash flow that an acquirer can believe. The plan you write at the start is the same document that makes the exit possible at the end.

And it connects, through Entrepreneurship itself, to **Family Business Succession** — a succession plan is a business plan for the transfer of management, leadership, and ownership, which is why the textbooks note that most succession failures are relational rather than financial, and why the plan is only part of it.


## The mathematics

The mathematical heart of a business plan is arithmetic — adding and subtracting, multiplying and dividing. You are not doing any algebra or calculus; you are counting money and customers. The three core calculations are: (1) Cost of goods sold (COGS) — what does it cost you to make one unit of your product? Add raw materials, direct labour, and any other cost that only exists when you make a unit. (2) Revenue — price per unit times number of units sold. (3) Profit — revenue minus all costs. But there is a subtlety: some costs are fixed (they do not change whether you sell one unit or a thousand — like rent), and some are variable (they change with each unit — like the cost of ingredients). A simple way to reason about this is break-even analysis: how many units must you sell to cover all fixed costs? The formula is: break-even units = fixed costs ÷ (price per unit − variable cost per unit). The difference (price − variable cost) is called the contribution margin, because each sale contributes that much towards covering fixed costs. Once fixed costs are covered, all further contribution is profit. This is pure arithmetic — no symbols needed, just careful multiplication and division.

Break-even point (in units) = Fixed Costs ÷ (Price per unit − Variable Cost per unit)

Where:
- Fixed Costs: Costs that do not change with output (rent, salaries, insurance)
- Price per unit: The selling price of one unit
- Variable Cost per unit: The cost of making one more unit (materials, direct labour)
- The denominator (Price per unit − Variable Cost per unit) is called the contribution margin per unit.


## A worked example

```
Imagine a small bakery. Fixed costs per month: rent Rs 20,000, salaries Rs 30,000, utilities Rs 5,000 — total fixed costs Rs 55,000. Variable cost per loaf: flour, yeast, packaging, electricity for the oven — Rs 25 per loaf. Selling price: Rs 60 per loaf. We want to know how many loaves must be sold each month to avoid a loss.

Step 1: Price − variable cost = 60 − 25 = 35 Rs per loaf (contribution margin)   # Each loaf sold contributes Rs 35 towards covering fixed costs.
Step 2: Fixed costs ÷ contribution margin = 55,000 ÷ 35 = 1,571.4 loaves   # So about 1,572 loaves must be sold each month just to break even.
Step 3: 1,572 loaves ÷ 30 days = 52.4 loaves per day   # If the bakery is open 30 days a month, it must sell about 53 loaves daily. This is a quick sanity check: is a neighbourhood bakery likely to sell that many? If not, the plan is unviable.
Step 4: If you sell 2,000 loaves in a month: revenue = 2,000 × 60 = 120,000; total variable cost = 2,000 × 25 = 50,000; total cost = 50,000 + 55,000 = 105,000; profit = 120,000 − 105,000 = 15,000 Rs   # Above break-even, each extra loaf adds Rs 35 to profit. With modest growth, the bakery becomes profitable.

Result: The bakery needs about 1,572 loaves per month to break even, which is about 53 loaves a day. This is a realistic target for a small bakery, suggesting the venture is worth pursuing if the location can attract that volume. The plan would then refine this by seasonality, pricing changes, or cost reduction.
```


## Common misconceptions

**The plan is a document for investors** — I'm starting a small stall with my own savings — I don't need to write a plan because I'm not pitching investors.

The main audience for a business plan is not the investor — it is you. The plan is a thinking tool that forces every assumption out of your head and into numbers where it can be tested. An investor reads the plan after it has already saved you from the worst of your own overly optimistic estimates. In fact: The plan is for you, first. Investors may read it later, but its primary job is to clarify your thinking before you spend money on anything.

**The plan is the outcome** — I've written a 40-page business plan, so now I can launch — the plan is done and the business is ready.

You wrote the plan and you did not talk to a single customer or price a single ingredient. The plan is a hypothesis, not a proof. It becomes useful only when it is used to guide conversations and changed as a result of them. In fact: The plan is a living document. You update it weekly with what you learn from real customers, real suppliers, and real revenue. The document is never 'done'; only the thinking improves.

**Everyone who writes a plan succeeds** — I've written the plan, so the business will work — the plan says we break even in month three.

A plan is a set of assumptions, not a guarantee. It does not make the market appear if the market is not there. It does not make customers pay a price they will not pay. In fact: A plan is a test of assumptions, not a promise. It tells you what needs to be true for the business to work — your job is to go out and check each assumption, and abandon or revise the plan when reality disagrees.

**Only big businesses need plans** — I'm just starting a small catering business from home — I don't need a boardroom-style business plan.

Small businesses fail precisely because they skip planning for the boring parts. A small catering business still has customers, a cost structure, and a cash flow cycle — and it has even less margin for error than a big company. In fact: The size does not change the logic. Every business, however small, has a market, a model, operations and financials — and writing down each of those, even on one page, is what catches the fatal flaw before it becomes a loss.


## In short

A business plan is not a document you write for investors — it is a thinking discipline you use on yourself. The content matters less than the act of writing it down: naming your customer, pricing your offer, counting your costs, projecting your cash flow, and then testing each assumption against reality. The value is in the reasoning it forces; the pages are just the fossil record of that reasoning. If you remember only one thing: revise it constantly. The plan is a map of a moving jungle — draw it, and redraw it, and the jungle stops being a mystery.


## Where this is used

Business plan writing is a business skill, not an AI-system-building skill — but the discipline has specific, concrete intersections with the way AI systems are built in a startup or small-business context.

First, in **ordinary applied machine learning** — the most common AI use case in a small business is forecasting and classification. A churn model, a sales forecast, a loan default classifier. The business plan is where you define the problem that the model will solve, and — more importantly — the plan is what tells you whether a model is even worth building. A model that predicts customer churn by 5 percentage points is only valuable if the plan has already established what those 5 points are worth in revenue. The financial projections in the plan — how many customers, at what lifetime value — are the unit economics that the ML business case is anchored to. A developer building this ML system will first ask: 'what does one prediction improve, in rupees, according to the plan?' If the plan does not exist, the ML work is unfunded and unjustified.

In **large language models**, the business plan is how you decide whether and how to use them. Do you build your own fine-tuned model on developer infrastructure — the plan's operations and cost section will tell you whether it makes sense, against what you would gain in accuracy. Do you instead call OpenAI's or Anthropic's APIs, paying per token — the plan's unit economics tell you whether the per-call cost leaves you any margin on the customer. For a business writing a plan for an AI-powered product, the plan forces the make-or-buy decision into the open: build your own model (rarely the right answer for a small business, because the compute and data costs overwhelm the per-call fees), or use an existing API (usually right, if the plan's margins survive the token cost).

In **small language models that run on devices** — a phone, a laptop, an edge device — the plan comes into play at the design stage. A model that must run on a phone has a hard constraint on size and compute: it cannot be the 70-billion-parameter monster. The plan is what captures the market decision first: who is the user? Are they offline? Do they need privacy on-device, or is a cloud round-trip acceptable? The plan's market and operations sections answer this. A startup building a voice assistant for rural farmers with intermittent connectivity will write a plan that says: the product must work offline. The engineering team then trains a small model that fits in a few megabytes. The plan drives this design decision; it is the 'user has no internet' constraint in the requirements document that the AI team encodes.

In **retrieval-augmented generation (RAG)** — the technology behind enterprise AI that answers questions by retrieving documents and feeding them to an LLM — the business plan plays the role of the 'knowledge base.' A RAG system is only as good as the documents it retrieves. For a business building on RAG, the plan is one of the most important documents to be retrieved. An AI assistant for a company's sales team, asked 'what is the pricing policy for a large enterprise deal?', will retrieve the old pricing decks, the email chain where the policy changed, and the business plan that contains the unit economics and margin targets. The plan is the source of truth the RAG system pulls from. When they ask 'can we afford a 20% discount?', the retrieved plan's financials are what the model will reason about. A startup developing a RAG-based product for small businesses will, in its own plan, identify that the value proposition is 'answer questions from your planning documents,' which means their software's usefulness depends on whether its customers write plans at all.

In **agentic systems** — agents that plan, call tools, and act in loops to achieve a goal — the business plan is, ironically, one of the best test beds. An agent designed to help an entrepreneur validate a business idea would: take the plan sections (market, financials, operations), identify the assumptions in them, and call a tool to check them. For example, the agent's first action might be 'the plan assumes 500 samosas per day at ₹20 each — call the Census of India API for the station footfall, and call the wholesaler pricing API for potato and oil costs.' The agent then updates the plan with real numbers. Building this agent is a concrete way to test how an agentic system of tool-calling and data-fetching actually behaves — exactly the kind of capability that enterprise customers increasingly pay for. A developer building such an agent will write code that parses the plan document, extracts figures, checks them against external data sources via APIs, and rewrites the plan — all of which is a practical, if ordinary, exercise in agent engineering.

What building software with it looks like in practice: a developer building a business-planning tool uses a library like **pdfplumber** or **pypdf** to parse the plan document, **pandas** to load the financial tables, and an LLM API to summarise or critique the narrative. The frameworks are the same as any document-processing pipeline: the document is read, the tables are extracted, the numbers are stored in a data structure, and the LLM generates analysis. What breaks when it is done badly: if the parsing is brittle — the plan is a collection of ragged PDFs and Google Docs, not one clean file — the extraction fails silently, the numbers are wrong, and the agent concludes the business is profitable when it is not. An agent that confidently tells an entrepreneur 'you will break even in month two' from a misparsed table is worse than no agent at all. The discipline of the plan — fixed sections, labelled tables, consistent financials — is what makes the AI tooling possible. A well-structured plan is a machine-readable asset; a messy one is just paper.


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Read this on the web: https://basavapurushottam.com/learn-ai/business-plan-writing
